复合材料拉托力预测中标准差加权融合算法  

Composite rato capacity prediction of standard deviation of weighted fusion algorithm

作　　者：李盼[1] 杨风暴[1] 王肖霞[1] 樊庆英[1] 

机构地区：[1]中北大学信息与通信工程学院,山西太原030051

出　　处：《电子测试》2012年第3期1-3,68,共4页Electronic Test

基　　金：国家自然科学基金项目(61171057);山西省自然基金项目(2011011015-1);山西省研究生创新项目(20103082)

摘　　要：拉托力是判断复合材料的粘接强度的一个重要指标,针对金属与非金属粘接复合材料的粘接强度检测,提出基于标准差加权融合算法可预测其拉托力,最后根据数理统计预测出拉托力的范围。多传感器数据融合是充分利用多传感器资源,消除单个或少量传感器的局限性。为了能够准确利用各个传感器的数值,减少传感器之间的数据冗余,先将传感器按照声阵列方式放置,再将各个传感器进行多次测量取其标准差,对其标准差所占的权重进行加权融合。融合表明,该算法简单且可以提高拉托力的预测精度。To determine the bond strength of composite materials, rato force is is an important indicator, for metal and non-adhesive bond strength of composite materials testing, proposed fusion algorithm based on the weighted standard deviation and can predict its rato force, the final prediction the rato force range based on mathematical statistics. Multi sensor data fusion is to make full use of multi sensor resources, eliminate the limitation of single or a small amount sensor. In order to accurately use various sensor values, reduced between the sensor data redundancy, the first sensor according to the acoustic array placement, then each sensor measurement of many times the standard deviation, the standard deviation of the weights of weighted fusion.Ntegration shows that the algorithm is simple and can improve the prediction accuracy of rato force.

关 键 词：多传感器 数据融合 数理统计 拉托力预报 

分 类 号：TB33[一般工业技术—材料科学与工程]